Your QA team is buried in write-ups, not investigations
A deviation needs a clear description, an impact assessment and links to related events. A CAPA needs evidence from several systems. Most of the effort goes to gathering and formatting, and overdue deviations become an inspection observation of their own.
- Deviation reports vary in quality and structure from author to author
- Finding similar past deviations and CAPAs is slow
- SOP changes ripple into forms, training requirements and related SOPs
What we build
Deviation drafting
Drafts a structured deviation description from the initial report and linked records, in your template, for the owner to complete and approve.
Similar-event search
Searches past deviations, CAPAs and complaints by product, process step or failure mode, so investigators can spot repeats.
SOP revision support
Drafts proposed SOP changes and lists every document, form and training requirement tied to the changed section.
CAPA evidence packages
Assembles the records a CAPA or effectiveness check needs into one package, sources linked, for QA review.
How it works
Step 1: Define intended use and risk
With your QA lead, we document what each function does, what it doesn't, and its risk, supporting a risk-based approach such as CSA.
Step 2: Connect with least privilege
The tool reads from your eQMS and document systems with scoped access. It can't approve, close or modify controlled records.
Step 3: Draft, then human review
AI output enters your workflow as a draft. The record owner edits and approves it under your procedures and e-signatures.
Step 4: Audit trail by design
Reviewers see the AI's output, its sources and every human change, with user and timestamp.
Systems we connect
These are capabilities, not shipped connectors. We scope each one during Discovery.
- eQMS platforms
- SharePoint and Microsoft 365 document libraries
- Training management (LMS) systems
- ERP lot and inventory data where relevant, such as NetSuite
Reference
Our VP of AI Engineering, Michael Fethe, spent 15 years inside publicly traded agriculture and life science corporations. We bring that experience together with the documentation, audit-trail and private-deployment patterns we've built for regulated manufacturing and finance clients.
Related work outside life science: we planned a compliance-aware AI deployment for a registered investment adviser, with access controls, recordkeeping and human review designed in before anything was connected.
Questions QA leaders ask
Who validates the tool?
Your QA team. We supply documented intended use, defined access, audit trails and test evidence to support it. The validation decision belongs to your quality system.
Do you work with CSA or traditional CSV?
Either. Documented intended use and risk per function fit a CSA approach and feed a CSV package. Your QA team picks the method.